Skip to content

Instantly share code, notes, and snippets.

@b1nary
b1nary / enterpreneur-quotes.json
Created July 14, 2015 22:20
325 Enterpreneur Quotes as JSON
[
{
"text":"The only people who never fail are those who never try.",
"from":"Ilka Chase"
},
{
"text":"Failure is just another way to learn how to do something right.",
"from":"Marian Wright Edelman"
},
{
/*
* Copyright 2026 Kyriakos Georgiopoulos
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
@ashwch
ashwch / git-worktrees-zero-to-hero.md
Last active May 15, 2026 15:33
Git Worktrees: From Zero to Hero - A comprehensive guide to using Git worktrees with submodules
@imba-tjd
imba-tjd / .Cloud.md
Last active May 15, 2026 15:33
☁️ 一些免费的云资源

  • IaaS指提供系统(可以自己选)或者储存空间之类的硬件,软件要自己手动装。PaaS提供语言环境和框架(可以自己选)。SaaS只能使用开发好的软件(卖软件本身,如税务会计、表格文字处理)。BaaS一般类似于非关系数据库,但各家不通用
  • 云服务的特点:零前期成本 & 按需付费 & 弹性(类似于租,可随时多加、退掉;但没有残值)、高可用(放在机房中,不同AZ间水电隔离)

如果你想补充内容,建议优先给 free-for-dev 提PR,还能混个高星repo的contributor,没必要加到本列表里。
If you want to make improvements, I would recommend you contributing to free-for-dev rather than this list.

其他人的集合

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

@acidgreenservers
acidgreenservers / AGENTS.md
Last active May 15, 2026 15:31
System Prompt For Coding Agents.

CODEBASE REASONING TOPOLOGY (Short)

You are a thinking partner for experienced developers. Your role is to help them think clearer, design better systems, and ship coherent code — not to teach or act as a blind code generator.

Core Truth: Structure is persistence. Prioritize tight topology over perfect context.


ENTRY PROTOCOL: Ambiguity Detection

@jlia0
jlia0 / agent loop
Last active May 15, 2026 15:29
Manus tools and prompts
You are Manus, an AI agent created by the Manus team.
You excel at the following tasks:
1. Information gathering, fact-checking, and documentation
2. Data processing, analysis, and visualization
3. Writing multi-chapter articles and in-depth research reports
4. Creating websites, applications, and tools
5. Using programming to solve various problems beyond development
6. Various tasks that can be accomplished using computers and the internet
@FNGarvin
FNGarvin / Easiest Possible Image Generation.md
Last active May 15, 2026 15:28
Easiest Possible Image Generation

The EASIEST way to get going creating images RIGHT NOW is with stable-diffusion.cpp. It has no external dependencies, so you don't have to fight Python or torch. Download the cuda binaries and exe if you have NVidia or otherwise grab this for Vulkan that runs on Intel, NVidia, and AMD.

Unzip and it should look something like this:image

Download some models to the same folder. Getting these three would be a good start: model, vae, llm.

Write a batch

@ruvnet
ruvnet / goal-planner.md
Last active May 15, 2026 15:27
Claude GOAL

name: goal-planner description: "Goal-Oriented Action Planning (GOAP) specialist that dynamically creates intelligent plans to achieve complex objectives. Uses gaming AI techniques to discover novel solutions by combining actions in creative ways. Excels at adaptive replanning, multi-step reasoning, and finding optimal paths through complex state spaces. Examples: Context: User needs to optimize a complex workflow with many dependencies. user: 'I need to deploy this application but there are many prerequisites and dependencies' assistant: 'I'll use the goal-planner agent to analyze all requirements and create an optimal action sequence that satisfies all preconditions and achieves your deployment goal.' Complex multi-step planning with dependencies requires the goal-planner agent's GOAP algorithm to find the optimal path. Context: User has a high-level goal but isn't sure of the steps. user: 'Make my application production-ready' assistant: 'I'll use th